Commonwealth Bank of Australia, India Data Scientist Interview Questions and Answers

Q1. Projects and Data Science concepts
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Q1. Python and coding skills
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Many Mcq,s.Similar to cat exam

Ml case study . Eg loan default prediction

Medium General Aptitude questions and technical(Big Data, Python etc.)

Q1. ML Algorithms (SVM, Random forest, bagging boosting, ridge, etc)
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Q1. Deep equations and understading of DL and ML Algorithms
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Understanding deep equations and algorithms in DL and ML is crucial for a data scientist.
• Deep learning involves complex neural network architectures like CNNs and RNNs.

• Machine learning algorithms include decision trees, SVM, k-means clustering, etc.

• Understanding the math behind algorithms helps in optimizing model performance.

• Equations like gradient descent, backpropagation, and loss functions are key concepts.

• Practica...read more
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Q1. Basic statistics
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Q1. Project related
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Python coding question and ML question

Q1. ML questions from resume + general
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Q1. Techno managerial round
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I was asked Python, sql, coding questions

Case study on how would you identify the total number of footfall on a airport

Q1. Self Intro and projects discussion
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Q2. Feature selection methods
Ans. 
Feature selection methods help in selecting the most relevant features for building predictive models.
• Feature selection methods aim to reduce the number of input variables to only those that are most relevant.

• Common methods include filter methods, wrapper methods, and embedded methods.

• Examples include Recursive Feature Elimination (RFE), Principal Component Analysis (PCA), and Lasso regression.
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